Partha Pratim Pande
Papers
2
Total Citations
15
H-Index
2
About
Partha Pratim Pande is a leading researcher at the intersection of energy-efficient computing and embedded systems, with a primary focus on enabling complex artificial intelligence on resource-constrained edge devices. His work addresses the critical challenge of deploying deep neural networks (DNNs) for applications like self-driving cars, mobile health, and augmented/virtual reality—tasks traditionally relegated to the cloud. Pande’s major contributions include developing a general hardware and software co-design framework for energy-efficient Edge AI (2021, 12 citations), which provides a foundational methodology for optimizing both computational and power resources in real-time, on-device processing. He has also advanced the field of 3D object reconstruction from images on mobile platforms through his work on PETNet (2020, 3 citations), a Graph Convolution Network-based approach that balances polygon count and energy trade-offs. This innovation is particularly impactful for AR/VR and robotics, where efficient 3D rendering is essential. Pande’s research is notable for its practical, system-level perspective, bridging algorithmic innovation with hardware constraints to make intelligent, autonomous systems more accessible and sustainable.
Research Focus
Key Achievements
Top Papers
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- 2